Panagiotis Sismanidis

Assessing the Capability of a Downscaled Urban Land Surface Temperature Time Series to Reproduce the Spatiotemporal Features of the Original Data

The downscaling of frequently-acquired geostationary Land Surface Temperature (LST) data can compensate the lack of high spatiotemporal LST data for urban climate studies. In order to be usable, the generated datasets must accurately reproduce the spatiotemporal features of the coarse-scale LST time series with greater spatial detail. This work concerns this issue and exploits the high temporal resolution of the data to address it. Specifically, it assesses the accuracy, correct pattern formation and the spatiotemporal inter-relationships of an urban three-month-long downscaled geostationary LST time series. The results suggest that the downscaling process operated in a consistent manner and preserved the radiometry of the original data. The exploitation of the data inter-relationships for evaluation purposes revealed that the downscaled time series reproduced the smooth diurnal cycle, but the autocorrelation of the downscaled data was higher than the original coarse-scale data. Overall, the evaluation process showed that the generation of high spatiotemporal LST data for urban areas is very challenging, and to deem it successful, it is mandatory to assess the temporal evolution of the urban thermal patterns. The results suggest that the proposed tests can facilitate the evaluation process.

Evaluating the Operational Retrieval and Downscaling of Urban Land Surface Temperatures

The Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory (NOA/IAASARS) has developed a system that retrieves and downscales thermal remote sensing data obtained from Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) in real time. This activity aims to facilitate the operational monitoring of the urban thermal environment by providing sharpened data in a timely manner. The system entered its operational phase in April 2014 by producing quarter-hourly land surface temperature (LST) data at an enhanced spatial resolution (1 km) for five major European cities. The current work briefly presents the system and exhaustively validates the generated time-series for the three summer months of 2014. The performance assessment was carried out by comparing the entire archive of generated LST data (i.e., more than 30 000 images) with similar independent and well-validated products. The results obtained indicate that both the LST retrieval and LST downscaling modules, which form the heart of the system, perform satisfactorily. The wealth of information made available through such exploitation of MSG-SEVIRI imagery in real time has the potential to fill a large gap in monitoring the thermal urban environment and support effectively the timely generation of higher value products and services related to energy demand and heat-related health issue.

An Online System for Nowcasting Satellite Derived Temperatures for Urban Areas

The Urban Heat Island (UHI) is an adverse environmental effect of urbanization that increases the energy demand of cities and impacts human health. The study of this effect for monitoring and mitigation purposes is crucial, but it is hampered by the lack of high spatiotemporal temperature data. This article presents the work undertaken for the implementation of an operational real-time module for monitoring 2 m air temperature (TA) at a spatial resolution of 1 km based on the Meteosat Second Generation—Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI). This new module has been developed in the context of an operational system for monitoring the urban thermal environment. The initial evaluation of TA products against meteorological in situ data from 15 cities in Europe and North Africa yields that its accuracy in terms of Root Mean Square Error (RMSE) is 2.3 °C and Pearson’s correlation coefficient (Rho) is 0.95. The temperature information made available at and around cities can facilitate the assessment of the UHIs in real time but also the timely generation of relevant higher value products and services for energy demand and human health studies. The service is available at http://snf-652558.vm.okeanos.grnet.gr/treasure/portal/info.html.

Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels

The downscaling of geostationary diurnal thermal data can ease the lack of land surface temperature (LST) datasets that combine high spatial and temporal resolution. However, the downscaling of diurnal LST data is more demanding than single scenes. This is because the spatiotemporal interrelationships of the original LST data have to be preserved and accurately reproduced by the downscaled LST (DLST) data. To that end, LST disaggregation kernels/predictors that provide information about the spatial distribution of LST during different times of a day can prove especially useful. Such LST predictors are the LST Annual Cycle Parameters (ACPs). In this work, multitemporal ACPs are employed for downscaling daytime and nighttime ~4 km geostationary LST from SEVIRI (Spinning Enhanced Visible and Infrared Imager) down to 1 km. The overall goal is to assess if the use of the ACPs can improve the estimation of the diurnal range of DLST (daytime DLST minus nighttime DLST). The evaluation is performed by comparing the DLST diurnal range maps with reference data from MODIS (Moderate Imaging Spectroradiometer) and also with data retrieved from a modified version of the TsHARP (Thermal Sharpening) algorithm. The results suggest that the ACPs increase the downscaling performance, improve the estimation of diurnal DLST range and produce more accurate spatial patterns.

De-shadowing of airborne imagery using at-sensor downwelling irradiance data

Cast shadows caused by sparse clouds usually degrade spaceborne and airborne imagery. They result from the decrease of the direct solar beam due to the presence of a non-transparent cloud. The reduction of the downwelling solar flux density can be quantified during an air campaign, if the aircraft flies beneath the cloud and is equipped with an add-on instrument that measures the total downwelling solar irradiance. The objective of this work is to exploit such data for the de-shadowing of airborne hyperspectral imagery. Initially, the specific illumination and viewing conditions during the image acquisition, which allow the use of at-sensor downwelling irradiance data for the de-shadowing of airborne hyperspectral imagery, are outlined. Then a methodology is proposed that estimates the radiometric enhancement coefficients from the at-sensor irradiance data and correlates them with the image data using a shadow map. Improvements of the quality of the shadow maps are suggested. Performance assessment showed that at-sensor irradiance data could be satisfactorily utilized for compensating the cast shadow effects on remotely sensed imagery. It also highlighted the importance of generating and using an accurate shadow map and the particular difficulties for the air campaign planning raised by the requirement of exploitable at-sensor irradiance data.

Mapping the Spatiotemporal Dynamics of Europe’s Land Surface Temperatures

The land surface temperature (LST) drives many terrestrial biophysical processes and varies rapidly in space and time primarily due to the earth’s diurnal and annual cycles. Models of the diurnal and annual LST cycle retrieved from satellite data can be reduced to several gap-free parameters that represent the surface’s thermal characteristics and provide a generalized characterization of the LST temporal dynamics. In this letter, we use such an approach to map Europe’s annual and diurnal LST dynamics. In particular, we reduce a five-year time series (2009–2013) of diurnal LST from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to 48 sets of half-hourly annual cycle parameters (ACPs), namely, the mean annual LST, the yearly amplitude of LST, and the LST phase shift from the spring equinox. The derived data provide a complete representation of how mainland Europe responds to the heating of the sun and the nighttime LST decay and reveal how Europe’s biogeographic regions differ in that respect. We further argue that the SEVIRI ACP can provide an observation-based spatially consistent background for studying and characterizing the thermal behavior of the surface and also a data set to support climate classification at a finer spatial resolution.

Towards real time quarter-hour monitoring of the urban thermal environment at sharpened spatial resolution

In recent years, the importance of monitoring the spatial and temporal characteristics of the Surface Urban Heat Island (SUHI) phenomenon has increased due to the rapid growth of the urban population. A system for real time and online monitoring of the urban thermal environment, which exploits the fine temporal resolution (15 min) of Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI), at a spatial resolution of 1 km, is being developed at the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens (IAASARS/NOA). The system utilizes a large number of global ancillary data, and comprises four separate major modules, namely: satellite image acquisition; nowcasting and very short range forecasting; land surface temperature (LST) derivation; and LST downscaling. Initially the system will cover the Institute host city of Athens, Greece, one of the eight Group on Earth Observations (GEO), Task SB-04 Supersites. However, the overall goal is to expand its coverage to every city observed by MSG-SEVIRI with a population larger that one million. This system will fill a large gap in data availability for SUHI studies, since no high spatial and temporal resolution data are acquired on a systematic basis. Furthermore, it will also provide a framework for further research and the development of numerous applications.

Evaluation of atmospheric correction to airborne hyperspectral data relying on radiative transfer concepts

Physically based atmospheric correction is one of the most important but also perilous radiometric corrections in remote-sensing imagery. The main objective of this work was to evaluate the efficiency of atmospheric correction algorithms, based not only on quantification of the changes induced but also on a step-by-step interpretation of the results, in association with the radiative transfer (RT) processes that occur in the atmosphere and on Earth. A four-level atmospheric correction scheme was applied to airborne hyperspectral visible/near-infrared (VNIR) imagery and the performance was evaluated. Each atmospheric correction level was more numerous than the previous following adjunctive assessment of the following parameters: (1) atmospheric influence, (2) the adjacency effect, (3) cast shadows, and (4) effects induced by the Earth’s surface reflectance anisotropy. Performance assessment showed that, even though a more complex atmospheric correction scheme resembles in greater detail the conditions under which the image acquisition was carried out, it is more sensitive to restrictions that arise from either the sensor’s characteristics or the algorithms and data used. Moreover, it was shown that evaluating atmospheric correction results using criteria based on RT concepts can considerably assist in the evaluation process.

Diurnal analysis of surface Urban Heat Island using spatially enhanced satellite derived LST data

The importance of studying the Urban Heat Island (UHI) phenomenon has increased over the years due to the processes of urbanization and industrialization. Thermal remote sensing imagery has been extensively utilized for surface UHI (SUHI) studies. However, the low image acquisition frequency of most sensors limits its use. The Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, of the National Observatory of Athens (NOA/IAASASRS) has developed a system that produces land surface temperature (LST) time series by downscaling data retrieved from MSGSEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) geostationary satellite. The system has been designed specifically to facilitate urban climate studies, by producing LST datasets that combine high spatial and temporal resolution. Moreover, the large number of LST image data produced, enables their utilization to a number of different applications. In this work, LST data from the NOA/IAASARS system have been employed for the study of the diurnal evolution of the SUHI phenomenon for Athens (GR), Istanbul (TR) and Rome (IT). The results obtained refer to the summer of 2014 and highlight the intensity and temporal variation of this phenomenon for each city employed in this study.

Real-time appraisal of the spatially distributed heat related health risk and energy demand of cities

The Urban Heat Island (UHI) is an adverse environmental effect of urbanization that increases the energy demand of cities, impacts the human health, and intensifies and prolongs heatwave events. To facilitate the study of UHIs the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens (IAASARS/NOA) has developed an operational real-time system that exploits remote sensing image data from Meteosat Second Generation – Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) and generates high spatiotemporal land surface temperature (LST) and 2 m air temperature (TA) time series. These datasets form the basis for the generation of higher value products and services related to energy demand and heat-related health issues. These products are the heatwave hazard (HZ); the HUMIDEX (i.e. an index that describes the temperature felt by an individual exposed to heat and humidity); and the cooling degrees (CD; i.e. a measure that reflects the energy needed to cool a building). The spatiotemporal characteristics of HZ, HUMIDEX and CD are unique (1 km/5 min) and enable the appraisal of the spatially distributed heat related health risk and energy demand of cities. In this paper, the real time generation of the high spatiotemporal HZ, HUMIDEX and CD products is discussed. In addition, a case study corresponding to Athens’ September 2015 heatwave is presented so as to demonstrate their capabilities. The overall aim of the system is to provide high quality data to several different end users, such as health responders, and energy suppliers. The urban thermal monitoring web service is available at http://snf-652558.vm.okeanos.grnet.gr/treasure/portal/info.html.